ABSTRACT NUMBER: ESOC2026A1004 CEREBRAL SMALL VESSEL DISEASE-RELATED STRUCTURAL DIFFERENCES IN CORTICAL GREY MATTER NETWORKS ARE LINKED TO COGNITIVE FUNCTION AND VASCULAR RISK FACTORS

Abstract Background and aims Cerebral small vessel disease (CSVD) is a key driver of vascular cognitive impairment. While typically captured as disruptions in white matter integrity, its impact on cortical grey matter organization remains incompletely understood. We applied Morphometric INverse Divergence (MIND), a novel neuroimaging technique that computes brain networks from anatomical MRI, to explore CSVD-related grey matter signatures in association with cognitive function and vascular risk factors. Methods We analyzed cross-sectional multimodal brain MRI and clinical data from 3913 participants of the Hamburg City Health Study (HCHS). CSVD burden was quantified as white matter hyperintensity (WMH) load, Fazekas scores, perivascular space (PVS) counts, and peak width of skeletonized mean diffusivity (PSMD). Single-subject cortical similarity networks were constructed using MIND, which estimates connectivity between cortical regions based on their structural profile derived from T1-weighted MRI. We utilized multivariate statistics to link CSVD pathology to MIND network architecture and correlated the resulting pattern with cognitive assessments as well as cardiovascular risk factors (Figure 1 and 2). Results We identified a significant multivariate association between CSVD and structural differences in cortical profiles. Notably, this latent pattern characterized by reduced CSVD burden alongside higher MIND similarity was linked to better cognitive test performances and lower vascular risk, and vice versa (Figure 3). Conclusions By investigating structural grey matter alterations, we demonstrated that CSVD is not limited to white matter injury but extends to cortical networks. Moreover, MIND network analysis provided an avenue for novel mechanistic insights linking vascular pathology, brain architecture, and cognitive impairment. Conflict of interest J. Gallinat reports speaker fees from Lundbeck, Janssen-Cilag, Lilly, Otsuka, and Boehringer outside the submitted work. G. Thomalla has received fees as consultant or lecturer from Acandis, Alexion, Amarin, Bayer, Boehringer Ingelheim, BristolMyersSquibb/Pfizer, Daichi Sankyo, Portola, and Stryker outside the submitted work. All other authors report nothing to disclose. Figure 1 - belongs to Methods Figure 2 - belongs to Methods Figure 3 - belongs to Results

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Journal
European Stroke Journal
Published
2026-05-01
DOI
https://doi.org/10.1093/esj/aakag023.511
Primary Topic
Neurological Disease Mechanisms and Treatments
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article
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article

ABSTRACT NUMBER: ESOC2026A1004 CEREBRAL SMALL VESSEL DISEASE-RELATED STRUCTURAL DIFFERENCES IN CORTICAL GREY MATTER NETWORKS ARE LINKED TO COGNITIVE FUNCTION AND VASCULAR RISK FACTORS

Bastian Cheng, Märit Jensen, Eckhard Schlemm, Marvin Petersen et al.
European Stroke Journal
Neurological Disease Mechanisms and Treatments
article

ABSTRACT NUMBER: ESOC2026A1004 CEREBRAL SMALL VESSEL DISEASE-RELATED STRUCTURAL DIFFERENCES IN CORTICAL GREY MATTER NETWORKS ARE LINKED TO COGNITIVE FUNCTION AND VASCULAR RISK FACTORS

Bastian Cheng, Märit Jensen, Eckhard Schlemm, Marvin Petersen, Simone Kuehn, Max Bieder, David Emskötter, Felix Nägele, Götz Thomalla, Jürgen Gallinat
article en

Abstract

Abstract Background and aims Cerebral small vessel disease (CSVD) is a key driver of vascular cognitive impairment. While typically captured as disruptions in white matter integrity, its impact on cortical grey matter organization remains incompletely understood. We applied Morphometric INverse Divergence (MIND), a novel neuroimaging technique that computes brain networks from anatomical MRI, to explore CSVD-related grey matter signatures in association with cognitive function and vascular risk factors. Methods We analyzed cross-sectional multimodal brain MRI and clinical data from 3913 participants of the Hamburg City Health Study (HCHS). CSVD burden was quantified as white matter hyperintensity (WMH) load, Fazekas scores, perivascular space (PVS) counts, and peak width of skeletonized mean diffusivity (PSMD). Single-subject cortical similarity networks were constructed using MIND, which estimates connectivity between cortical regions based on their structural profile derived from T1-weighted MRI. We utilized multivariate statistics to link CSVD pathology to MIND network architecture and correlated the resulting pattern with cognitive assessments as well as cardiovascular risk factors (Figure 1 and 2). Results We identified a significant multivariate association between CSVD and structural differences in cortical profiles. Notably, this latent pattern characterized by reduced CSVD burden alongside higher MIND similarity was linked to better cognitive test performances and lower vascular risk, and vice versa (Figure 3). Conclusions By investigating structural grey matter alterations, we demonstrated that CSVD is not limited to white matter injury but extends to cortical networks. Moreover, MIND network analysis provided an avenue for novel mechanistic insights linking vascular pathology, brain architecture, and cognitive impairment. Conflict of interest J. Gallinat reports speaker fees from Lundbeck, Janssen-Cilag, Lilly, Otsuka, and Boehringer outside the submitted work. G. Thomalla has received fees as consultant or lecturer from Acandis, Alexion, Amarin, Bayer, Boehringer Ingelheim, BristolMyersSquibb/Pfizer, Daichi Sankyo, Portola, and Stryker outside the submitted work. All other authors report nothing to disclose. Figure 1 - belongs to Methods Figure 2 - belongs to Methods Figure 3 - belongs to Results

European Stroke JournalVol. 11(Supplement_1)
Universität Hamburg (DE), University Medical Center Hamburg-Eppendorf (DE)
Openalex Percentile: Top 9%
Neurological Disease Mechanisms and Treatments
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